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Related papers: Towards quantitative precision in functional QCD I

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Approximate computing techniques have been successful in reducing computation and power costs in several domains. However, error sensitive applications in high-performance computing are unable to benefit from existing approximate computing…

Numerical Analysis · Mathematics 2021-05-04 James Diffenderfer , Daniel Osei-Kuffuor , Harshitha Menon

This paper is the first attempt to build CGC/saturation model based on the next-to-leading order corrections to linear and non-linear evolution in QCD. We assume that the renormalization scale is the saturation momentum and found that the…

High Energy Physics - Phenomenology · Physics 2016-12-28 Carlos Contreras , Eugene Levin , Rodrigo Meneses , Irina Potashnikova

The renormalization group plays an essential role in many areas of physics, both conceptually and as a practical tool to determine the long-distance low-energy properties of many systems on the one hand and on the other hand search for…

Statistical Mechanics · Physics 2021-05-10 N. Dupuis , L. Canet , A. Eichhorn , W. Metzner , J. M. Pawlowski , M. Tissier , N. Wschebor

We present a functional renormalization group (fRG) study of the two dimensional Hubbard model, performed with an algorithmic implementation which lifts some of the common approximations made in fRG calculations. In particular, in our fRG…

Strongly Correlated Electrons · Physics 2019-10-23 Agnese Tagliavini , Cornelia Hille , Fabian B. Kugler , Sabine Andergassen , Alessandro Toschi , Carsten Honerkamp

Linear regression and classification methods with repeated functional data are considered. For each statistical unit in the sample, a real-valued parameter is observed over time under different conditions related by some neighborhood…

Methodology · Statistics 2024-09-23 Issam-Ali Moindjié , Cristian Preda , Sophie Dabo-Niang

Quantum-inspired classical algorithms has received much attention due to its exponential speedup compared to existing algorithms, under certain data storage assumptions. The improvements are noticeable in fundamental linear algebra tasks.…

Quantum Physics · Physics 2025-12-08 Hyunho Cha , Jungwoo Lee

Functional renormalization group (FRG) has become a diverse and powerful tool to derive effective low-energy scattering vertices of interacting many-body systems. Starting from a non-interacting expansion point of the action, the flow of…

Strongly Correlated Electrons · Physics 2014-01-22 Johannes Reuther , Ronny Thomale

First quantized, grid-based methods for chemistry modelling are a natural and elegant fit for quantum computers. However, it is infeasible to use today's quantum prototypes to explore the power of this approach, because it requires a…

Quantum Physics · Physics 2023-03-09 Hans Hon Sang Chan , Richard Meister , Tyson Jones , David P. Tew , Simon C. Benjamin

When causal quantities cannot be point identified, researchers often pursue partial identification to quantify the range of possible values. However, the peculiarities of applied research conditions can make this analytically intractable.…

Methodology · Statistics 2021-09-29 Guilherme Duarte , Noam Finkelstein , Dean Knox , Jonathan Mummolo , Ilya Shpitser

Several topics in QCD are reviewed, including: the light-cone Fock state representation, which encodes the flavor, spin and other quark and gluon correlations of hadrons in the form of universal process-independent amplitudes; the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Stanley J. Brodsky

The search for new physics requires a joint experimental and theoretical effort. Lattice QCD is already an essential tool for obtaining precise model-free theoretical predictions of the hadronic processes underlying many key experimental…

In this paper, we present a novel approach for conformal prediction (CP), in which we aim to identify a set of promising prediction candidates -- in place of a single prediction. This set is guaranteed to contain a correct answer with high…

Machine Learning · Computer Science 2021-02-03 Adam Fisch , Tal Schuster , Tommi Jaakkola , Regina Barzilay

We propose the formulation of lattice QCD wherein all elements of the theory (gauge action, fermionic action, theta-term, and all operators) are constructed from a single object, namely the lattice Dirac operator D with exact chiral…

High Energy Physics - Lattice · Physics 2007-05-23 Ivan Horvath

We evaluate all two-point correlation functions of the Curci-Ferrari (CF) model in four dimensions and in the presence of mass-degenerate fundamental quark flavors, as a natural extension of an earlier investigation in the quenched…

High Energy Physics - Theory · Physics 2021-12-01 Nahuel Barrios , John A. Gracey , Marcela Peláez and , Urko Reinosa

The predictive power of perturbative QCD (pQCD) depends on two important issues: (1) how to eliminate the renormalization scheme-and-scale ambiguities at fixed order, and (2) how to reliably estimate the contributions of unknown…

High Energy Physics - Phenomenology · Physics 2019-03-27 Bo-Lun Du , Xing-Gang Wu , Jian-Ming Shen , Stanley J. Brodsky

This thesis is about new methods of achieving RG transformations, in both a continuum spacetime background and on a lattice discretization thereof. The subject is explored from the point of view of euclidean quantum field theory. As a…

High Energy Physics - Lattice · Physics 2020-06-16 Andrea Carosso

A primary problem for perturbative QCD analyses is how to set the renormalization scale of the QCD running coupling in order to achieve maximally precise fixed-order predictions for physical observables. The Principle of Maximum…

High Energy Physics - Phenomenology · Physics 2015-11-06 Xing-Gang Wu , Sheng-Quan Wang , Stanley J. Brodsky

We evaluate thermodynamic observables such as pressure, baryon number, entropy and energy density, as well as the second and fourth order baryon number cumulants in the phase structure of QCD. The intertwined confinement and chiral dynamics…

High Energy Physics - Phenomenology · Physics 2025-04-08 Yi Lu , Fei Gao , Yu-xin Liu , Jan M. Pawlowski

In this study, we propose a function-on-function linear quantile regression model that allows for more than one functional predictor to establish a more flexible and robust approach. The proposed model is first transformed into a…

Methodology · Statistics 2021-11-11 Ufuk Beyaztas , Han Lin Shang

We propose a computationally simple framework for clustering functional data based on Gaussian-process-generated random projections. In this approach, each curve is first projected onto a large collection of independent Gaussian process…

Methodology · Statistics 2026-05-22 Sourav Chakrabarty , Anirvan Chakraborty , Shyamal K. De
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